Population scale data reveals the antidepressant effects of ketamine and other therapeutics approved for non-psychiatric indications

The study evaluates population-scale data for clarity on the antidepressant effects of ketamine and other therapeutics approved for non-psychiatric indications. It shows that patients with ketamine demonstrated a significantly lower frequency of reports of depression, pain, and opioid-induced side effects, as compared to patients who used other combinations of drugs for pain. The conclusion supported ketamine’s potential in pain management pharmacotherapy.

Abstract

“Current therapeutic approaches to depression fail for millions of patients due to lag in clinical response and non-adherence. Here we provide new support for the antidepressant effect of an anesthetic drug, ketamine, by Inverse-Frequency Analysis of eight million reports from the FDA Adverse Effect Reporting System. The results of the examination of population scale data revealed that patients who received ketamine had significantly lower frequency of reports of depression than patients who took any other combination of drugs for pain. The analysis also revealed that patients who took ketamine had significantly lower frequency of reports of pain and opioid induced side effects, implying ketamine’s potential to act as a beneficial adjunct agent in pain management pharmacotherapy. Further, the Inverse-Frequency Analysis methodology provides robust statistical support for the antidepressant action of other currently approved therapeutics including diclofenac and minocycline.”

Authors: Isaac V. Cohen, Tigran Makunts, Rabia Atayee & Ruben Abagyan

Summary

The standard of care of depression treatment consists of five main classes of antidepressants, serotonin reuptake inhibitors (SSRIs) being the most common. However, nearly half of psychiatric and primary care patients discontinue their antidepressant therapy prematurely due to late onset of beneficial outcomes, lack of efficacy, adverse reactions, fear of drug dependence, and lack of mechanisms to enforce adherence.

Because of problems with treatment resistant depression (TRD) patients, some clinicians have been driven to utilize other drugs, such as ketamine, for treatment. This study used the FDA Adverse Event Reporting System (FAERS) postmarketing database to look for statistically significant values of the negative log odds ratio.

Ketamine patients had significantly lower frequency of reports of depression than patients who took any other combination of drugs for pain. Ketamine is known to be much more rapid than current antidepressants.

The analysis of the whole FAERS database revealed several other unintentional depression reducing drugs among antibiotics, cosmeceuticals and NSAIDS. Ketamine patients had the lowest depression event rates compared to patients who received any other combination of drugs for pain excluding NSAIDs.

Figure 1 shows the frequency of adverse events in patients on FAERS who took ketamine and the odds ratios for pain and depression event rates, constipation, vomiting, and nausea event rates.

Ketamine is used for depression, and may also be used for pain management. It has been shown to have opioid-sparing properties and may provide benefits of improved pain, reduced requirement of opioids, and ultimately less opioid reduced side effects.

This study supports previous small scale studies’ conclusions that ketamine is a good monotherapy or adjunct therapy for depression, and that it has therapeutic potential for TRD. It also demonstrates a methodology for discovering off label pharmacology of existing approved drugs.

Methods

The FDA Adverse Event Reporting System (AERS) database contains reports of adverse reactions and medication errors sent to the FDA through MedWatch.

By combining FAERS and AERS quarterly reports in dollar separated text format, a consistent table field structure was produced.

Over 8 million adverse event reports were combined into a master file, and all synonyms, capitalizations, and misspellings were recognized and assigned to a single value.

The study used data from two databases, FAERS and AERS, and only a subset of actual cases was used. However, the combined set of records had provided sufficient statistical power for the analysis.

Comparative Statistics were performed on patient cohorts with adverse event report rates. The Odds Ratio and Log Odds Ratio were calculated.

Standard Error and 95% Confidence Interval were calculated for Figs 1b, 1c, 1d, and 2, and the LogOR was calculated for Figs 1c, 1d, and 2.

Acknowledgements

This work was funded by University of California San Diego Skaggs School of Pharmacy and Pharmaceutical Sciences and involves the Abagyan lab.

Additional Information

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